| anomaly-detection-on-btad | UniNet | #1 | Detection AUROC: 97.73Segmentation AUROC: 97.70… |
| anomaly-detection-on-mvtec-ad | UniNet | #2 | Detection AUROC: 99.90Segmentation AUPRO: 96.00… |
| anomaly-detection-on-ucsd-ped2 | UniNet | #6 | AUC: 97.9 |
| anomaly-detection-on-visa | UniNet | #1 | Detection AUROC: 99.8Segmentation AUPRO (until 30% FPR): 93.9… |
| anomaly-detection-on-visa | UniNet(model-unified multi-class) | #3 | Detection AUROC: 99.15F1-Score: 98.29 |
| image-classification-on-isic2018 | UniNet | #1 | Accuracy: 100.0F1: 100.0 |
| medical-image-segmentation-on-cvc-clinicdb | UniNet | #16 | mean Dice: 0.942mIoU: 0.895 |
| medical-image-segmentation-on-cvc-colondb | UniNet | #4 | mean Dice: 0.919mIoU: 0.856 |
| medical-image-segmentation-on-kvasir-seg | UniNet | #25 | mean Dice: 0.915mIoU: 0.857 |
| retinal-oct-disease-classification-on-oct2017 | UniNet | #1 | Acc: 100.0 |